1 edition of Parallel Image Processing found in the catalog.
|Statement||by Thomas Bräunl, Stefan Feyrer, Wolfgang Rapf, Michael Reinhardt|
|Contributions||Feyrer, Stefan, Rapf, Wolfgang, Reinhardt, Michael|
|The Physical Object|
|Format||[electronic resource] /|
|Pagination||1 online resource (ix, 203 p.)|
|Number of Pages||203|
|ISBN 10||3642086799, 3662043270|
|ISBN 10||9783642086793, 9783662043271|
Summary. Exploring theories and applications developed during the last 30 years, Digital Geometry in Image Processing presents a mathematical treatment of the properties of digital metric spaces and their relevance in analyzing shapes in two and three dimensions. Unlike similar books, this one connects the two areas of image processing and digital geometry, . The book offers a selection of sixteen revised papers originally presented at the International Conference on Parallel Image Processing , held in Paris, France, June , At this occcasion, several international researchers, mainly from France, India, Italy, Japan, and the USA, joined in order to present their theoretical and practical investigations on parallel image .
Thesis Title: Pixel-Parallel Image Processing Techniques and Algorithms Declaration to be completed by the candidate: I declare that no portion of this work referred to in this thesis has been submitted in support of an application for another degree or qualification of this or any other university or other institute of learning. Author: Ravishankar Chityala,Sridevi Pudipeddi; Publisher: CRC Press ISBN: Category: Technology & Engineering Page: View: DOWNLOAD NOW» Image Processing and Acquisition using Python provides readers with a sound foundation in both image acquisition and image processing—one of the first books to integrate these topics .
I am doing some image processing but I have a lot of images (~10,). Thus I would like to do it in parallel but for some reason it does not go as fast as . Digital Image Processing by Gonzalez is the basic book that contains all the fundamentals of the book. I read that book and got much depth into the subject. As far as i know image processing is not confined to a single book. Get a book and you can.
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This book introduces the area of image processing and data-parallel processing. It covers a number of standard algorithms in image processing and describes their parallel implementation.
The programming language chosen for all examples is a structured parallel programming language which is ideal for educational by: This book developed out of a series of publications in the area of image processing with massively parallel algorithms.
The topic of Parallel Image Processing book processing is a particularly promising area for the use of synchronous massively parallel or data-parallel compu ter systems which work according to the SIMD principle (single instruction, multiple data).
Parallel Image Processing | This book introduces the area of image processing and data-parallel processing. It covers a number of standard algorithms in image processing and describes their parallel implementation.
This book developed out of a series of publications in the area of image processing with massively parallel algorithms. The topic of image processing is a particularly promising area for the use of. This book introduces the world of image processing and data-parallel processing.
It covers quite a few commonplace algorithms in image processing and describes their parallel implementation. The programming language chosen for all examples is a structured parallel programming language which is true for educational features.
This book introduces the area of image processing and data-parallel processing. It covers a number of standard algorithms in image processing and describes their parallel implementation. The programming language chosen for all examples is a structured parallel programming language which is ideal for educational purposes.
It examines a complete library of standard image processing operations and analyzes their implementation in a data-parallel context. The book starts with point operators and local operations such as edge dection, corner detection and morphology, then continues to Hough and Fourier transforms and also includes stereo image and image sequence processing.
We develop parallel image processing algorithms for hypercube and reconfigurable mesh (RMESH) architectures.
The problems considered are shrinking, expanding, clustering, template matching, histogramming, Hough transform, computation of. Image processing, Image synthesis, Virtual reality Petroleum Virtual prototyping Biology and genomics Enterprise App.
J2EE and Web servers Business Intelligence Banking, Finance, Insurance, Risk Analysis Regression tests for large software Storage and Access to large logs Security: Finger Print matching, Image behavior recognition 5.
Parallel Recognition of High Dimensional Images (M Nivat & A Saoudi) Two-Dimensional Uniquely Parsable Isometric Array Grammars (Y Yamamoto & K Morita) Replicated Image Algorithms and Their Analyses on SIMD Machines (P J Narayanan & L S Davis) The Depth and Motion Analysis Machine (O D Faugeras et al.).
This paper proposes the SunwayImg, a parallel image processing library, to support image-related applications on the Sunway many-core processor as well as the Sunway TaihuLight supercomputer. The SunwayImg integrates three kinds of image algorithms: fundamental algorithms to support basic image operations on the Sunway processor, widely used image Author: Rui Liu, Yi Liu, Meiting Zhao, Kaida Song, Depei Qian.
Image Processing and Pattern Recognition Based on Parallel Shift Technology - CRC Press Book This book describes the methods and algorithms for image pre-processing and recognition. These methods are based on a parallel shift technology of the imaging copy, as well as simple mathematical operations to allow the generation of a minimum set of features to describe and.
Image analysis on massively parallel computers: an architectural point of view / A. Mérigot and B. Zavidovique --Stealth terrain navigation for multi-vehicle path planning / Y. Ansel Teng, Daniel Dementhon and Larry S.
Davis --Implementation of the Z-buffer algorithm on a reconfigurable network of processors / Jian-Jin Li, Serge Miguet and. That’s the eBook of the printed book and shouldn’t embrace any media, website entry codes, or print dietary dietary supplements which can come packaged with the positive book.
For packages in Image Processing and Laptop Imaginative and prescient. Completely self-contained—and intently illustrated—this introduction to main concepts and.
This book serves as a general introduction to the area of image processing as well as to data-parallel processing. It covers a number of standard algorithms in image processing and describes their parallel implementation in a practical "hands-on" approach: Each algorithm is accompanied by numerous diagrams and program source code.
Book Description. This book describes the methods and algorithms for image pre-processing and recognition. These methods are based on a parallel shift technology of the imaging copy, as well as simple mathematical operations to allow the generation of a minimum set of features to describe and recognize the image.
This chapter reviews basic work on parallel image processing and analysis, with emphasis on work done at the Computer Vision Laboratory at the University of Maryland.
It describes parallel computers suitable for image processing tasks, including meshes, pyramids, and hypercubes, and discusses parallel algorithms for pixel-level and region-level Cited by: The applications presented may be considered representative of type of problems faced by signal and image processing researchers.
This chapter will also strive to serve as a guide to new signal and image processing parallel programmers, by suggesting a parallelization strategy that can be employed when developing a general parallel by: 9.
In parallel, the research domain of optical image processing has matured, potentially bypassing the problems digital approaches were suffering and bringing new applications.
The advancement of technology calls for applications and knowledge at the intersection of both areas but there is a clear knowledge gap between the digital signal. This book will touch the core of image processing, from concepts to code using Python.
The book will start from the classical image processing techniques and explore the evolution of image processing algorithms up to the recent advances in image processing or computer vision with deep learning.
Optical computing techniques for parallel image processing Abstract: Optical signal processing (OSP) offers numerous advantages in real time image processing applications.
OSP inherently offers parallelism in the processing of data at speeds much higher than those achievable using electrical digital signal processing (DSP).Author: J.M.H.
Elmirghani. Main purpose of this review is to provide the comparative study of the existing contributions of implementing parallel image processing applications with .There are six sections in this book.
The first section presents basic image processing techniques, such as image acquisition, storage, retrieval, transformation, filtering, and parallel computing. Then, some applications, such as road sign recognition, air quality monitoring, remote sensed image analysis, and diagnosis of industrial parts are considered.
Subsequently, the application of image.